Comparative analysis reveals trade-offs in acoustic performance and environmental impacts of CLT floor systems, indicating optimization potential.
This article discusses a design methodology that considers the development of a sound insulation prediction tool, using an artificial neural networks, and life cycle assessment analysis. 112 sound insulation measurements are employed to develop the prediction model. They are lab-based measurements and are performed on 45 various CLT- and ribbed CLT-based assemblies. The acoustic model demonstrates satisfactory results with 1 dB differences in the prediction of airborne and impact sound indices (R?? and L??,??). An acoustic sensitivity study and a statistical analysis are then conducted to validate the model's results. Additionally, an LCA analysis is performed on the floor assemblies to calculate their environmental footprints. LCA categories are plotted against the acoustic performance of floors. No correlations are found, and the results emphasize that a wide range of sound insulation can be achieved with similar environmental impacts. Within each acoustic performance tier, the LCA results can be optimized for a floor assembly by selecting appropriate materials. Designers should be cognizant of the trade-offs between acoustic insulation, and environmental performance when choosing assemblies with favorable environmental impacts.
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Eddin et al. (2025) studied this question.
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